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Curriculum Learning for Reinforcement Learning is an increasingly popular technique that involves training an agent on a sequence of intermediate tasks, called a Curriculum, to increase the agent's performance and learning speed.
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Burrhus Frederic Skinner · 1951
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Accurate monotonicity preserving cubic interpolation
James M Hyman · 1983
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Learning and development in neural networks: The importance of starting small
Jeffrey L Elman · 1993
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Policy transfer using reward shaping
Tim Brys, Anna Harutyunyan, Matthew E Taylor, and Ann Nowé · 2015
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Half field offense: An environment for multiagent learning and ad hoc teamwork
Matthew Hausknecht, Prannoy Mupparaju, and Sandeep Subramanian · 2016
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Source task creation for curriculum learning
Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone · 2016
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Prioritized experience replay
Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver · 2016
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Reverse curriculum generation for reinforcement learning
Carlos Florensa, David Held, Markus Wulfmeier, Michael Zhang, and Pieter Abbeel · 2017
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Teacher-student curriculum learning
Tambet Matiisen, Avital Oliver, Taco Cohen, and John Schulman · 2017
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Autonomous task sequencing for customized curriculum design in reinforcement learning
Sanmit Narvekar, Jivko Sinapov, and Peter Stone · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Object-oriented curriculum generation for reinforcement learning
Felipe Leno Da Silva and Anna Helena Reali Costa · 2018
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Stable baselines
Ashley Hill, Antonin Raffin, Maximilian Ernestus, Adam Gleave, Anssi Kanervisto, Rene Traore, Prafulla Dhariwal, Christopher Hesse, Oleg Klimov, Alex Nichol, Matthias Plappert, Alec Radford, John Schulman, Szymon Sidor, and Yuhuai Wu · 2018
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Learning by playing solving sparse reward tasks from scratch
Martin Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom van de Wiele, Vlad Mnih, Nicolas Heess, and Jost Tobias Springenberg · 2018
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An optimization framework for task sequencing in curriculum learning
Francesco Foglino, Christiano Coletto Christakou, and Matteo Leonetti · 2019
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Learning curriculum policies for reinforcement learning
Sanmit Narvekar and Peter Stone · 2019
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Self-paced deep reinforcement learning
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Automatic curriculum graph generation for reinforcement learning agents
M Svetlik, M Leonetti, J Sinapov, R Shah, N Walker, and P Stone · 2017
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Curriculum learning for cumulative return maximization
F Foglino, C Coletto Christakou, R Luna Gutierrez, and M Leonetti
Cited in the paper.
Pascal Klink, Carlo D' Eramo, Jan R Peters, and Joni Pajarinen · 2020
Closest in time.
Curriculum learning for reinforcement learning domains: A framework and survey
Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E Taylor, and Peter Stone · 2020
Closest in time.